Increasingly, driver assistance systems are used in vehicles which assist the driver in keeping the vehicle in its lane. Assistance systems warning the driver of an unintended departure from the vehicle lane are referred to in English as lane departure warning systems (LDWS). Systems which can intervene in the steering process directly are referred to in English as lane keeping systems (LKS). In German, these systems are generally referred to as lane keeping assistance systems (Spurhalteassistenzsysteme).
Lane keeping assistance systems are normally able to detect the lane in front of a vehicle (so called lane detection), i.e. in particular the course of the road. In particular the lane width, the horizontal and/or vertical curvature of the road, the lateral offset relative to the center of the lane and the pitch and yaw angles of the vehicle are estimated by the lane keeping assistance systems. From these system quantities the time can be calculated until the vehicle departs from the lane, and the driver can be warned of an unintended departure from the lane or the vehicle can be kept in its lane by electric steering or a specific ESP (electronic stability program) intervention.
The above-mentioned system quantities can be determined in particular by digital image processing of the situation in front of a vehicle, captured with an optical sensor, for example a CMOS camera. For this purpose a specific image processing algorithm is used, which evaluates structures in the captured images which are characteristic of a vehicle lane and its course, in particular roadway markings. The correct functioning of a lane keeping assistance system based on such image processing depends mainly on the fact that in the captured digital images the structures which are essential for lane detection, such as roadway markings, are detected in a reliable and precise manner. Normally, monochrome cameras are used to capture the images. The grayscale-value-based lane detection algorithms used for evaluating the images detect markings in the captured monochrome images mainly due to the dark-light/light-dark transitions between the road and the roadway markings. However, a reliable detection of the markings is ensured only for light markings on a dark ground, and not necessarily for colored markings, the grayscale value of which in the image is below the grayscale value of the ground or the road. For example, in the U.S. road sections are marked using dark yellow markings on a light ground and in Germany construction sites are indicated by yellow markings, and in Austria dark red markings are used on a light ground. These markings are very well visible to the human eye; not so, however, to a lane detection system using a monochrome camera, since the color impression is an optical one.
DE 10 2004 061 822 A1, which is incorporated by reference, shows a method for the detection of roadway markings, in particular in the area of construction sites, wherein the roadway markings are present in the form of image coordinates which are determined from a colored image of the surroundings of a motor vehicle. Here, yellow and white roadway markings are identified based on saturation values and hue values.